• The Journal of Bigdata
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• v.6 no.2
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• pp.139-149
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• 2021

Ddareungi, a public bicycle service in Seoul, establishes itself as a means of daily transportation for citizens in Seoul. We speculated that the pattern of using Ddareungi may have changed since COVID-19. This study explores changes in using Ddareungi after COVID-19 with descriptive statistical analysis and network analysis. The analysis results are summarized as follows. The average traveling distance and average traveling speed have decreased over the entire time in a day since COVID-19. The round trip rate has increased at dawn and morning and has decreased in the evening and night. The average weighted degree and average clustering coefficient have decreased, and the modularity has increased. The clusters, located north of the Han River in Seoul, had a similar geographic distribution before and after COVID-19. However, the clusters, located south of the Han River, had different geographic distributions after COVID-19. Traveling routes added to the top 5 traffic rankings after COVID-19 had an average traveling distance of fewer than 1,000 meters. We expect that the results of this study will help improve the public bicycle service in Seoul.

• Korean Journal of Agricultural and Forest Meteorology
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• v.8 no.4
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• pp.250-259
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• 2006

This study looks into forest fire occurrence hazards according to the change of temperature and humidity over thirty years at interval of ten days. We used data from the forest fire inventory from 1995 to 2004 and weather data such as average temperature and relative humidity for 30 years from 1971 to 2000. These data were expressed as a database with ten-day intervals for 76 weather stations. Forest fire hazards occurred in the spring season from the end of March to the middle of April. For the first step, the primitive surface of temperature and humidity was interpolated by IDW (the standard interpolation method). These thematic maps have a 1 km by 1 km grid spacing resolution. Next, we executed a simple regression analysis after extracting forest fire frequency, temperature and humidity values from 76 weather stations. The results produced a coefficient of determination ($R^2$) ranging from 0.4 to 0.6. Moreover, the estimation of forest fire occurrence hazards during early April was very high at Gyeongbuk Interior, Chungcheong Interior and part of Gangwon. The range of temperature and humidity having an influence on forest fire occurrence was as follows: average temperature and relative humidity in early April was $9-12^{\circ}C$ and 61-65%. At the end of March, temperature was $6-10^{\circ}C$, humidity 62-67%, and temperature was $11-14^{\circ}C$ and humidity 60-67% in the middle of April.

• Korean Journal of Agricultural and Forest Meteorology
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• v.2 no.2
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• pp.47-61
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• 2000

Agroclimatic zoning was done for paddy rice culture in North Korea based on a simulation experiment. Daily weather data for the experiment were generated by 3 steps consisting of spatial interpolation based on topoclimatological relationships, zonal summarization of grid cell values, and conversion of monthly climate data to daily weather data. Regression models for monthly climatological temperature estimation were derived from a statistical procedure using monthly averages of 51 standard weather stations in South and North Korea (1981-1994) and their spatial variables such as latitude, altitude, distance from the coast, sloping angle, and aspect-dependent field of view (openness). Selected models (0.4 to 1.6$^{\circ}C$ RMSE) were applied to the generation of monthly temperature surface over the entire North Korean territory on 1 km$\times$l km grid spacing. Monthly precipitation data were prepared by a procedure described in Yun (2000). Solar radiation data for 27 North Korean stations were reproduced by applying a relationship found in South Korea ([Solar Radiation, MJ m$^{-2}$ day$^{-1}$ ] =0.344 + 0.4756 [Extraterrestrial Solar Irradiance) + 0.0299 [Openness toward south, 0 - 255) - 1.307 [Cloud amount, 0 - 10) - 0.01 [Relative humidity, %), $r^2$=0.92, RMSE = 0.95 ). Monthly solar irradiance data of 27 points calculated from the reproduced data set were converted to 1 km$\times$1 km grid data by inverse distance weighted interpolation. The grid cell values of monthly temperature, solar radiation, and precipitation were summed up to represent corresponding county, which will serve as a land unit for the growth simulation. Finally, we randomly generated daily maximum and minimum temperature, solar irradiance and precipitation data for 30 years from the monthly climatic data for each county based on a statistical method suggested by Pickering et a1. (1994). CERES-rice, a rice growth simulation model, was tuned to accommodate agronomic characteristics of major North Korean cultivars based on observed phenological and yield data at two sites in South Korea during 1995~1998. Daily weather data were fed into the model to simulate the crop status at 183 counties in North Korea for 30 years. Results were analyzed with respect to spatial and temporal variation in yield and maturity, and used to score the suitability of the county for paddy rice culture.